Centre of Traditional Chinese Medicine Information Science and Technology, Shanghai University of T.C.M., Cailun Road 1200, Shanghai 201203, China.
Evid Based Complement Alternat Med. 2013;2013:695937. doi: 10.1155/2013/695937. Epub 2013 Jan 27.
Chronic hepatitis B (CHB) is a serious public health problem, and Traditional Chinese Medicine (TCM) plays an important role in the control and treatment for CHB. In the treatment of TCM, zheng discrimination is the most important step. In this paper, an approach based on CFS-GA (Correlation based Feature Selection and Genetic Algorithm) and C5.0 boost decision tree is used for zheng classification and progression in the TCM treatment of CHB. The CFS-GA performs better than the typical method of CFS. By CFS-GA, the acquired attribute subset is classified by C5.0 boost decision tree for TCM zheng classification of CHB, and C5.0 decision tree outperforms two typical decision trees of NBTree and REPTree on CFS-GA, CFS, and nonselection in comparison. Based on the critical indicators from C5.0 decision tree, important lab indicators in zheng progression are obtained by the method of stepwise discriminant analysis for expressing TCM zhengs in CHB, and alterations of the important indicators are also analyzed in zheng progression. In conclusion, all the three decision trees perform better on CFS-GA than on CFS and nonselection, and C5.0 decision tree outperforms the two typical decision trees both on attribute selection and nonselection.
慢性乙型肝炎（CHB）是一个严重的公共卫生问题，中医药在 CHB 的防治中发挥着重要作用。在中医药治疗中，辨证论治是最重要的一步。本文提出了一种基于 CFS-GA（基于相关性的特征选择和遗传算法）和 C5.0 提升决策树的方法，用于 CHB 中医药治疗中的辨证分类和进展。CFS-GA 的性能优于典型的 CFS 方法。通过 CFS-GA，获得的属性子集由 C5.0 提升决策树进行分类，用于 CHB 的中医药辨证分类，并且 C5.0 决策树在 CFS-GA、CFS 和非选择上的性能均优于 NBTree 和 REPTree 两种典型决策树。基于 C5.0 决策树的关键指标，通过逐步判别分析方法获得了辨证进展中的重要实验室指标，分析了辨证进展中重要指标的变化。总之，所有三种决策树在 CFS-GA 上的性能均优于 CFS 和非选择，并且 C5.0 决策树在属性选择和非选择上的性能均优于两种典型决策树。
